Network Coding for Energy Efficient Transmission in Wireless Body Area Networks

Conference paper


Talha, S, Ahmad, R, Kiani, A and Alam, MM (2017). Network Coding for Energy Efficient Transmission in Wireless Body Area Networks. The 7th International Conference on Current and Future Trends of Information and Communicaiton Technologies in Healthcare (ICTH 2017). Lund, Sweden 18 - 20 Sep 2017
AuthorsTalha, S, Ahmad, R, Kiani, A and Alam, MM
TypeConference paper
Abstract

Remote monitoring, early detection and prevention of diseases. Patients can be remotely monitored thanks to implant
devices in the body or by placing nodes on different parts of the body. Often the deployed sensor nodes are constraint
by limited battery sources and are required to continuously collect the data and transfer it to the sink node, thus
requiring energy efficient communication schemes. In addition, in poor channel conditions, this data collection and
transfer results in retransmission thus wasting useful energy. This work presents a cooperative network coding based
transmission technique for spectrum and energy efficiency in WBANs. The bit error rate (BER) of the network coded
path in comparison to direct communication approach is explored. The effect of WBAN path loss due to different node
positions is also discussed. It is observed that node position greatly affects path loss and received power which in turn
affect the BERs. Simulation results show that network coded cooperative communication strategy in WBAN channel
with and without combining outperforms as compared to direct communication.
© 2017 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the Conference Program Chairs.
Keywords: Wireless Body Area Networks; Cooperative Communication, Networks Coding; Energy Efficiency
* Corresponding author. Tel.: +0-000-000-0000 ; fax: +0-000-000-0000 .
E-mail address: muhammad.alam@ttu.ee
Available online at www.sciencedirect.com
ScienceDirect
Procedia Computer Science 00 (2017) 000–000
www.elsevier.com/locate/procedia
1877-0509 © 2017 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the Conference Program Chairs.
The 7th International Conference on Current and Future Trends of Information and
Communication Technologies in Healthcare (ICTH 2017)
Network Coding for Energy Efficient Transmission in Wireless
Body Area Networks
Sadaf Talhaa, Rizwan Ahmada, Adnan K. Kiania, Muhammad Mahtab Alamb*
aSchool of Electrical Engineering & Computer Science, National University of Sciences & Technology, Islamabad, Pakistan
bThomas Johann Seebeck Department of Electronics, School of Information Technology, Tallinn University of Technology, Ehitajate tee 5, 19086
Tallinn, Estonia
Abstract
Wireless Body Area Networks (WBANs) is a technology that has revolutionized the health-care industry by allowing
remote monitoring, early detection and prevention of diseases. Patients can be remotely monitored thanks to implant
devices in the body or by placing nodes on different parts of the body. Often the deployed sensor nodes are constraint
by limited battery sources and are required to continuously collect the data and transfer it to the sink node, thus
requiring energy efficient communication schemes. In addition, in poor channel conditions, this data collection and
transfer results in retransmission thus wasting useful energy. This work presents a cooperative network coding based
transmission technique for spectrum and energy efficiency in WBANs. The bit error rate (BER) of the network coded
path in comparison to direct communication approach is explored. The effect of WBAN path loss due to different node
positions is also discussed. It is observed that node position greatly affects path loss and received power which in turn
affect the BERs. Simulation results show that network coded cooperative communication strategy in WBAN channel with and without combining outperforms as compared to direct communication.

Year2017
Publisher's version
License
CC BY-NC-ND 4.0
Publication dates
Print18 Sep 2017
Publication process dates
Deposited11 Jan 2019
Accepted01 Jan 2017
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